Data Mining

SPSS Clementine 12.0

1. Clementine Overview

Clementine

1. Clementine Overview

Fall 2009Instructor: Dr. Masoud Yaghini

Outline

� Introduction

� Types of Models

� Clementine Interface

� References

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Introduction

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Introduction

� Three of the common data mining tools

– SPSS Clementine

– SAS-Enterprise Miner

– STATISTICA Data Miner

� The most popular and the oldest data mining tool

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package on the market today is SPSS Clementine

Introduction

� SPSS Clementine

– the most mature among the major data mining packages on

the market today.

� Since 1993, many thousands of data miners have used

Clementine to create very powerful models for

business.

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business.

� It was the first data mining package to use the

graphical programming user interface.

� It enables you to quickly develop data mining models

and deploy them in business processes to improve

decision making.

Introduction

� The Clementine package was integrated with CRISP-

DM to help guide the modeling process flow.

� Clementine supports the entire data mining process.

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Clementine Documentation

� Clementine User’s Guide

– General introduction to using Clementine.

� Clementine Source, Process, and Output Nodes

– Descriptions of all the nodes used to read, process, and output data in different

formats.

� Clementine Modeling Nodes

– Descriptions a variety of modeling methods in Clementine

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– Descriptions a variety of modeling methods in Clementine

� Clementine Applications Guide

– The examples in this guide provide brief, targeted introductions to specific

modeling methods and techniques.

� Clementine Algorithms Guide

– Descriptions of the mathematical foundations of the modeling methods used in

Clementine.

� CRISP-DM 1.0 Guide

– Step-by-step guide to data mining using the CRISP-DM methodology.

Application Examples

� While the data mining tools in Clementine can help

solve a wide variety of business and organizational

problems, the application examples provide brief,

targeted introductions to specific modeling methods

and techniques.

You can access the examples by choosing Application

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� You can access the examples by choosing Application

Examples from the Help menu in Clementine Client.

� The data files and sample streams are installed in the

Demos folder under the product installation directory.

Demos Folder

� The data files and sample streams used with the

application examples are installed in the Demos folder

under the product installation directory.

� This folder can also be accessed from the Clementine

12.0 program group under SPSS Inc on the Windows

Start menu.

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Start menu.

Changing the Temp Directory

� Some operations performed by Clementine may

require temporary files to be created.

� By default, Clementine uses the system temporary

directory to create temp files.

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Changing the Temp Directory

� To alter the location of the temporary directory using the

following steps:

– Create a new directory called clem and subdirectory called servertemp.

– Edit options.cfg, located in the /config directory of your Clementine

installation directory.

– Edit the temp_directory parameter in this file to read:

temp_directory, "C:/clem/servertemp".

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temp_directory, "C:/clem/servertemp".

– After doing this, you must restart the Clementine Server service. You

can do this by clicking the Services tab on your Windows Control

Panel. Just stop the service and then start it to activate the changes you

made. Restarting the machine will also restart the service.

– All temp files will now be written to this new directory.

Types of Models

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Types of Models

� In Clementine 12.0, models are packaged into

following modules:

– Classification module

� The Classification module helps organizations for prediction

– Association module

� Association models associate a particular conclusion (such as the

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� Association models associate a particular conclusion (such as the

decision to buy something) with a set of conditions.

– Segmentation module

� The Segmentation module is recommended in cases where the

specific result is unknown

Classification Module

� Classification module is included:

– Decision Trees

� C&R Tree

� QUEST

� CHAID

� C5.0

– Decision List

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– Decision List

– Neural Networks

– Regression

� Linear regression

� Logistic regression

– Bayesian Network

– Support Vector Machine (SVM)

Association Module

� Association module is included:

– Generalized Rule Induction (GRI)

– Apriori model

– CARMA model

– Sequence model

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Segmentation Module

� Clustering models focus on identifying groups of

similar records and labeling the records according to

the group to which they belong.

� This following models are included:

– K-Means

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– Kohonen

– TwoStep

– Anomaly Detection

Clementine Modules

� The following are optional add-on modules for

Clementine:

– Text Mining option for mining unstructured data

– Web Mining option

– Database Modeling for integration with other data mining

packages

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packages

Clementine Interface

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Starting Clementine

� To start the application, choose Clementine 12.0 from the SPSS

Inc program group on the Windows Start menu.

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Data Stream

� The Clementine interface employs an intuitive visual

programming interface to permit you to draw logical data

flows the way you think of them.

� Working with Clementine is a three-step process of working

with data.

– First, you read data into Clementine,

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– Then, run the data through a series of manipulations,

– And finally, send the data to a destination.

� This sequence of operations is known as a data stream

Stream Canvas

� Stream Canvas

– the largest area of the Clementine window and is where you

will build and manipulate data streams.

– You can work on multiple streams in the same canvas or

multiple stream files

– Streams are created by drawing diagrams of data operations

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– Streams are created by drawing diagrams of data operations

on the main canvas in the interface.

Clementine Interface

� Example of canvas:

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Clementine Interface

� Node

– Each operation is represented by an icon or node

– The nodes are linked together in a stream representing the

flow of data through each operation.

� Streams manager

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– streams are stored in the Streams manager, at the upper

right of the Clementine window.

Nodes Palette

� Nodes Palettes

– The palettes are groups of processing nodes listed across the bottom of

the screen.

– The palettes include Favorites, Sources, Record Ops (operations), Field

Ops, Graphs, Modeling, Output, and Export. When you click on one of

the palette names, the list of nodes in that palette is displayed below.

� the Record Ops palette tab.

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� the Record Ops palette tab.

� To add nodes to the canvas, double-click icons from the Nodes Palette or

drag and drop them onto the canvas.

Nodes Palette Tabs

� Nodes Palette Tabs

– Sources

� Nodes bring data into Clementine.

– Record Ops

� Nodes perform operations on data records, such as selecting,

merging, and appending.

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merging, and appending.

– Field Ops

� Nodes perform operations on data fields, such as filtering, deriving

new fields, and determining the data type for given fields.

– Graphs

� Nodes graphically display data before and after modeling. Graphs

include plots, histograms, web nodes, and evaluation charts.

Nodes Palette Tabs

� Nodes Palette Tabs

– Modeling

� Nodes use the modeling algorithms available in Clementine, such as

neural nets, decision trees, clustering algorithms, and data

sequencing.

– Output

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– Output

� Nodes produce a variety of output for data, charts, and model results,

which can be viewed in Clementine or sent directly to another

application, such as SPSS or Excel.

Clementine Managers

� The upper right window holds three managers:

– Streams

– Outputs

– Models

� You can switch the display of the manager window to

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show any of these items.

Clementine Managers

� Streams tab

– The Streams tab will display the active streams, which you can choose

to work on in a given session.

– You can use the Streams tab to open, rename, save, and delete the

streams created in a session.

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Clementine Managers

� Outputs tab

– The Output tab will show all graphs and tables output during a session.

– You can display, save, rename, and close the tables, graphs, and reports

listed on this tab.

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Clementine Managers

� Models tab

– The Models tab will show all the trained models you have created in the

session.

– These models can be browsed directly from the Models tab or added to

the stream in the canvas.

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Clementine Projects

� On the lower right side of the window is the projects

tool, used to create and manage data mining projects.

� There are two ways to view projects you create in

Clementine:

– The CRISP-DM view

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– The Classes view

Clementine Projects

� The CRISP-DM tab provides a way to organize projects

according to the CRISP-DM methodology.

� For both experienced and first-time data miners, using the

CRISP-DM tool will help you to better organize and

communicate your efforts.

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Clementine Projects

� The Classes tab provides a way to organize your work in

Clementine categorically—by the types of objects you create.

� This view is useful when taking inventory of data, streams, and

models.

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Clementine Toolbars

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Using Shortcut Keys

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Automating Clementine

� Since advanced data mining can be a complex and

sometimes lengthy process, Clementine includes

several types of coding and automation support. They

are:

– Clementine Language for Expression Manipulation

(CLEM)

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(CLEM)

– Scripting

– Batch mode

Automating Clementine

� Clementine Language for Expression Manipulation

(CLEM)

– is a language for analyzing and manipulating the data that

flows along Clementine streams.

– Data miners use CLEM extensively in stream operations to

perform tasks as simple as deriving profit from cost and

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perform tasks as simple as deriving profit from cost and

revenue data or as complex as transforming Web-log data

into a set of fields and records with usable information.

– For more information, see What Is CLEM? in Chapter 7 in

Clementine® 12.0 User’s Guide.

Automating Clementine

� Scripting

– is a powerful tool for automating processes in the user

interface and working with objects in batch mode.

– Scripts can perform the same kinds of actions that users

perform with a mouse or a keyboard.

– You can set options for nodes and perform derivations

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– You can set options for nodes and perform derivations

using a subset of CLEM.

– You can also specify output and manipulate generated

models.

– For more information, see Scripting Overview in Chapter 2

in Clementine® 12.0 Scripting and Automation Guide.

Automating Clementine

� Batch mode

– enables you to use Clementine in a non-interactive manner

by running Clementine with no visible user interface.

– Using scripts, you can specify stream and node operations

as well as modeling parameters and deployment options.

– For more information, see Introduction to Batch Mode in

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– For more information, see Introduction to Batch Mode in

Chapter 7 in Clementine® 12.0 Scripting and Automation

Guide.

References

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References

� Integral Solutions Limited., Clementine® 12.0 User’s

Guide, 2007.

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The end

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